目的 定量分析交通事故发展趋势,为城市交通事故精准防控提供决策支持。方法 通过采集某市2010—2020年高速公路交通事故相关数据,分析数据属性与交通事故关联度,基于ARIMA方法建立某市高速公路交通事故预测模型,结合指数回归曲线模型和灰色优化GOM模型的拟合度对比验证ARIMA模型可靠性。结果 基于离散性和随机性的交通事故时间序列数据,拟合建立的ARIMA(4,1,3)模型的预测结果精度达到94%以上,预测性能明显优于指数回归曲线模型和灰色优化GOM模型,模型有着良好可靠性与适用性。结论 基于ARIMA模型建立的交通事故预测模型对某市高速公路交通安全精细化管理具有一定的指导意义。

Objective To quantitatively analyze the development trend of traffic accidents and provide decision support for precise prevention and control of urban traffic safety management. Methods By collecting data related to highway traffic accidents in a certain city from 2010 to 2020,analyzing the correlation between data attributes and traffic accidents,a prediction model for highway traffic accidents in a certain city was established based on the ARIMA method.The reliability of the ARIMA model was verified by comparing the fit of the exponential regression curve model and the grey optimization GOM model. Results The prediction accuracy of the ARIMA (4,1,3) model established by fitting traffic accident time series data based on discreteness and randomness was over 94%,and the prediction performance was significantly better than the exponential regression curve model and the grey optimization GOM model.The model had good reliability and applicability. Conclusion The traffic accident prediction model established based on ARIMA model has certain guiding significance for the refined management of highway traffic safety in a certain city.